Combining strategies for the estimation of treatment effects
Autor(a) principal: | |
---|---|
Data de Publicação: | 2012 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Biblioteca Digital do Banco Nacional de Desenvolvimento Econômico e Social |
Texto Completo: | http://web.bndes.gov.br/bib/jspui/handle/1408/10614 |
Resumo: | Bibliografia: p. 68-71. |
id |
BNDES_954b7156da7057a586ae42ad85b8d056 |
---|---|
oai_identifier_str |
oai:web.bndes.gov.br:1408/10614 |
network_acronym_str |
BNDES |
network_name_str |
Biblioteca Digital do Banco Nacional de Desenvolvimento Econômico e Social |
repository_id_str |
https://web.bndes.gov.br/bib/jspui/?locale=pt_BR |
spelling |
Firpo, SergioPinto, Rafael de Carvalho Cayres2017-01-03T12:58:34Z2018-03-19T17:57:04Z2017-01-03T12:58:34Z2018-03-19T17:57:04Z2012-05FIRPO, Sergio; PINTO, Rafael de Carvalho Cayres. Combining strategies for the estimation of treatment effects. Brazilian Review of Econometrics, Rio de Janeiro, v. 32, n. 1, p. 31-71, maio 2012.http://web.bndes.gov.br/bib/jspui/handle/1408/10614Bibliografia: p. 68-71.The estimation of the average effect of a program or treatment on a variable of interest is an important tool for the assessment of economic policies. In general, assignment of potential participants to treatment does not occur at random and could thus generate a selection bias in absence of some correction. A way to get around this problem is by assuming that the econometrician observes a set of determinant characteristics of participation up to a strictly random component. Under such an assumption, the literature contains semiparametric estimators of the average treatment effect that are consistente and can asymptotically reach the semiparametric effciency bound. However, in frequently available samples, the performance of these methods is not always satisfactory. The aim of this paper is to investigate how the combination of two strategies may generate estimators with better properties in small samples. Therefore, we consider two ways of combining these approaches, based on the double robustness literature developed by James Robins et al. We analyze the properties of these combined estimators and discuss why they can outperform the separate use of each method. Finally, using a Monte Carlo simulation, we compare the performance of these estimators with that of the imputation and reweighting techniques. Our results show that the combination of strategies can reduce bias and variance, but this improvement depends on adequate implementation. We conclude that the choice of smoothing parameters is decisive for the performance of estimators in medium-sized samples.p. 31-71Sociedade Brasileira de EconometriaModelos econométricosEconometric modelsMonte Carlo, Método deMonte Carlo methodAnálise de regressãoRegression analysisCombining strategies for the estimation of treatment effectsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article5TextualProdução BNDESRio de Janeiroengreponame:Biblioteca Digital do Banco Nacional de Desenvolvimento Econômico e Socialinstname:Banco Nacional de Desenvolvimento Econômico e Social (BNDES)instacron:BNDESinfo:eu-repo/semantics/openAccessORIGINALCombining strategies for the estimation of treatment effects_Rafael Cayres_P_BD.pdfapplication/pdf441828http://web.bndes.gov.br/bib/jspui/bitstream/1408/10614/1/Combining%20strategies%20for%20the%20estimation%20of%20treatment%20effects_Rafael%20Cayres_P_BD.pdfd389693162224c23a263995d4508e55cMD51LICENSElicense.txttext/plain407http://web.bndes.gov.br/bib/jspui/bitstream/1408/10614/2/license.txtaeb6b64eb9f816a596cef5045906f205MD521408/106142023-04-19 17:10:05.943oai:web.bndes.gov.br: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Repositório Temáticohttps://web.bndes.gov.br/bib/jspui/PUBhttp://web.bndes.gov.br/bib/oai/requestbiblioteca.digital@bndes.gov.bropendoar:https://web.bndes.gov.br/bib/jspui/?locale=pt_BR2023-04-19T17:10:05Biblioteca Digital do Banco Nacional de Desenvolvimento Econômico e Social - Banco Nacional de Desenvolvimento Econômico e Social (BNDES)false |
dc.title.pt_BR.fl_str_mv |
Combining strategies for the estimation of treatment effects |
title |
Combining strategies for the estimation of treatment effects |
spellingShingle |
Combining strategies for the estimation of treatment effects Firpo, Sergio Modelos econométricos Econometric models Monte Carlo, Método de Monte Carlo method Análise de regressão Regression analysis |
title_short |
Combining strategies for the estimation of treatment effects |
title_full |
Combining strategies for the estimation of treatment effects |
title_fullStr |
Combining strategies for the estimation of treatment effects |
title_full_unstemmed |
Combining strategies for the estimation of treatment effects |
title_sort |
Combining strategies for the estimation of treatment effects |
author |
Firpo, Sergio |
author_facet |
Firpo, Sergio Pinto, Rafael de Carvalho Cayres |
author_role |
author |
author2 |
Pinto, Rafael de Carvalho Cayres |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Firpo, Sergio Pinto, Rafael de Carvalho Cayres |
dc.subject.por.fl_str_mv |
Modelos econométricos Econometric models Monte Carlo, Método de Monte Carlo method Análise de regressão Regression analysis |
topic |
Modelos econométricos Econometric models Monte Carlo, Método de Monte Carlo method Análise de regressão Regression analysis |
description |
Bibliografia: p. 68-71. |
publishDate |
2012 |
dc.date.issued.fl_str_mv |
2012-05 |
dc.date.accessioned.fl_str_mv |
2017-01-03T12:58:34Z 2018-03-19T17:57:04Z |
dc.date.available.fl_str_mv |
2017-01-03T12:58:34Z 2018-03-19T17:57:04Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
FIRPO, Sergio; PINTO, Rafael de Carvalho Cayres. Combining strategies for the estimation of treatment effects. Brazilian Review of Econometrics, Rio de Janeiro, v. 32, n. 1, p. 31-71, maio 2012. |
dc.identifier.uri.fl_str_mv |
http://web.bndes.gov.br/bib/jspui/handle/1408/10614 |
identifier_str_mv |
FIRPO, Sergio; PINTO, Rafael de Carvalho Cayres. Combining strategies for the estimation of treatment effects. Brazilian Review of Econometrics, Rio de Janeiro, v. 32, n. 1, p. 31-71, maio 2012. |
url |
http://web.bndes.gov.br/bib/jspui/handle/1408/10614 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
p. 31-71 |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Econometria |
publisher.none.fl_str_mv |
Sociedade Brasileira de Econometria |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital do Banco Nacional de Desenvolvimento Econômico e Social instname:Banco Nacional de Desenvolvimento Econômico e Social (BNDES) instacron:BNDES |
instname_str |
Banco Nacional de Desenvolvimento Econômico e Social (BNDES) |
instacron_str |
BNDES |
institution |
BNDES |
reponame_str |
Biblioteca Digital do Banco Nacional de Desenvolvimento Econômico e Social |
collection |
Biblioteca Digital do Banco Nacional de Desenvolvimento Econômico e Social |
bitstream.url.fl_str_mv |
http://web.bndes.gov.br/bib/jspui/bitstream/1408/10614/1/Combining%20strategies%20for%20the%20estimation%20of%20treatment%20effects_Rafael%20Cayres_P_BD.pdf http://web.bndes.gov.br/bib/jspui/bitstream/1408/10614/2/license.txt |
bitstream.checksum.fl_str_mv |
d389693162224c23a263995d4508e55c aeb6b64eb9f816a596cef5045906f205 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 |
repository.name.fl_str_mv |
Biblioteca Digital do Banco Nacional de Desenvolvimento Econômico e Social - Banco Nacional de Desenvolvimento Econômico e Social (BNDES) |
repository.mail.fl_str_mv |
biblioteca.digital@bndes.gov.br |
_version_ |
1813095373228474368 |